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Emotion Analyzer Bert GGUF
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Emotion Analyzer Bert GGUF

Developed by mradermacher
Static quantized version of BERT-based sentiment analysis model, supporting English text sentiment classification
Text Classification
Transformers
 EnglishOpen Source License:MIT#English Sentiment Classification#BERT Quantization#Multi-label Sentiment Analysis
Downloads 109
Release Time : 5/31/2025

Model Overview

This is a sentiment analysis model based on BERT architecture, specifically designed for English text sentiment classification. The model has been quantized, offering multiple quantization versions to accommodate different hardware requirements.

Model Features

Multiple Quantization Versions
Provides various quantization versions from Q2_K to Q8_0 to meet different performance and accuracy needs
Static Quantization
The model has undergone static quantization to optimize inference performance
Multi-label Classification
Supports multi-label sentiment classification for text

Model Capabilities

English text sentiment analysis
Multi-label classification
Multi-category classification

Use Cases

Social Media Analysis
User Comment Sentiment Analysis
Analyze the sentiment tendencies of user comments on social media
Can identify multiple sentiment labels
Customer Feedback Analysis
Product Review Classification
Perform sentiment classification on product reviews from e-commerce platforms
Helps businesses understand customer satisfaction
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